Hi I have special requirement when I need to process data in one partition at
the last after doing many filtering,updating etc in a DataFrame. Currently
to process data in one partition I am using coalesce(1) which is killing and
painfully slow my jobs hangs for hours even 5-6 hours and I dont know how to
solve this I came across localIterator will it be helpful in my case please
share some example if it is useful or please share me idea how to solve this
problem of processing data in one partition only. Please guide.
JavaRDD<Row> maksedRDD =
sourceRdd.coalesce(1,true).mapPartitionsWithIndex(new Function2<Integer,
Iterator<Row>, Iterator<Row>>() {
@Override
public Iterator<Row> call(Integer ind, Iterator<Row>
rowIterator) throws Exception {
List<Row> rowList = new ArrayList<>();
while (rowIterator.hasNext()) {
Row row = rowIterator.next();
List rowAsList =
updateRowsMethod(JavaConversions.seqAsJavaList(row.toSeq()));
Row updatedRow = RowFactory.create(rowAsList.toArray());
rowList.add(updatedRow);
}
return rowList.iterator();
}
}, false);
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